Buffered Steiner Trees for difficult instances

Buffer insertion has become an increasingly critical optimization in high performance design. The problem of finding a delay-optimal buffered Steiner tree has been an active area of research, and excellent solutions exist for most instances. However, current approaches fail to adequately solve a particular class of real-world "difficult" instances which are characterized by a large number of sinks, variations in sink criticalities, and varying polarity requirements. We propose a new Steiner tree construction called C-Tree for these instance types. When combined with van Ginneken style buffer insertion, C-Tree achieves higher quality solutions with fewer resources compared to traditional approaches

Buffered Steiner trees for difficult instances

Buffer insertion has become an increasingly critical optimization in high performance design. The problem of finding a delay-optimal buffered Steiner tree has been an active area of research, and excellent solutions exist for most instances. However, current approaches fail to adequately solve a particular class of real-world “difficult ” instances which are characterized by a large number of sinks, variations in sink criticalities, and varying polarity requirements. We propose a new Steiner tree construction called C-Tree for these instance types. When combined with van Ginneken style buffer insertion, C-Tree achieves higher quality solutions with fewer resources compared to traditional approaches. 1

Buffered Steiner Trees for Difficult Instances

With the rapid scaling of IC technology, buffer insertion has become an increasingly critical optimization technique in high performance design. The problem of finding a buffered Steiner tree with optimal delay characteristics has been an active area of research, and excellent solutions exist for most instances. However, there exists a class of real "difficult" instances which are characterized by a large number of sinks (e.g., 20-100), large variations in sink criticalities, non-uniform sink distribution, and varying polarity requirements. Existing techniques are either inefficient, wasteful of buffering resources, or unable to find a high-quality solution. We propose C-Tree, a two-level construction that first clusters sinks with common characteristics together, constructs low-level Steiner trees for each cluster, then performs a timing-driven Steiner construction on the top-level clustering. We show that this hierarchical approach can achieve higher quality solutions with fewer resources compared to traditional timing-driven Steiner trees